MongoDB and Python: Patterns and Processes for the Popular by Niall O'Higgins

Tips on how to leverage MongoDB along with your Python functions, utilizing the hands-on recipes during this e-book. You get whole code samples for initiatives comparable to making quick geo queries for location-based apps, successfully indexing your consumer files for social-graph lookups, and lots of different scenarios.

This consultant explains the fundamentals of the document-oriented database and exhibits you ways to establish a Python atmosphere with it. the right way to learn and write to MongoDB, follow idiomatic MongoDB and Python styles, and use the database with numerous well known Python internet frameworks. You'll observe easy methods to version your info, write powerful queries, and stay away from concurrency difficulties corresponding to race stipulations and deadlocks.

Approximately This Book
• Simplify layout trend implementation utilizing the ability of Python
• each one trend is followed with a real-world instance demonstrating its key features
• this is often an easy-to-follow consultant concentrating on the sensible elements of Python layout patterns

Who This e-book Is For
This publication is for Python programmers with an intermediate history and an curiosity in layout styles carried out in idiomatic Python. Programmers of different languages who're drawn to Python may also reap the benefits of this ebook, however it will be larger in the event that they first learn a few introductory fabrics that specify how issues are performed in Python.

What you are going to Learn
• discover manufacturing facility strategy and summary manufacturing unit for item creation
• Clone items utilizing the Prototype pattern
• Make incompatible interfaces appropriate utilizing the Adapter pattern
• safe an interface utilizing the Proxy pattern
• decide on an set of rules dynamically utilizing the method pattern
• expand an item with out subclassing utilizing the Decorator pattern
• maintain the common sense decoupled from the UI utilizing the MVC pattern

In Detail
Python is an object-oriented, scripting language that's utilized in wide variety of different types. In software program engineering, a layout trend is a suggested approach to a software program layout challenge. even supposing now not new, layout styles stay one of many most well-liked subject matters in software program engineering they usually come as a prepared reference for software program builders to resolve the typical difficulties they face at work.

This booklet will take you thru each layout trend defined with assistance from real-world examples. the purpose of the e-book is to introduce extra low-level aspect and ideas on the right way to write Pythonic code, not only targeting universal suggestions as applied in Java and C++. It comprises small sections on troubleshooting, top practices, approach structure, and its layout features. With the aid of this publication, it is possible for you to to appreciate Python layout trend ideas and the framework, in addition to matters and their answer. You'll specialise in all sixteen layout styles which are used to unravel daily difficulties.

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A useful begin to Computing with Python allows scholars to speedy research computing with no need to exploit loops, variables, and item abstractions in the beginning. Requiring no previous programming event, the booklet attracts on Python’s versatile information forms and operations in addition to its ability for outlining new services.

Extra info for MongoDB and Python: Patterns and Processes for the Popular Document-Oriented Database

Example text

Each of these can be performed atomically with the provided update modifiers. com" in the “emails” field. $pull will remove the entire document from the array in an atomic fashion, meaning there is no opportunity for a race condition. update({"username":"foouser"}, {"$pull":{"emails":{"primary":{"$ne":True}}}, safe=True) The full range of query modifiers (see table in Chapter 2) are available for use, including $gt, $lt and so on. Additionally, $pull can be used with arrays containing atoms (numbers, strings, dates, ObjectIDs etc).

For large collections, index creation can be time consuming. To help mitigate the impact of these operations on live, production databases, MongoDB is capable of building indexes in the background, without blocking database access. Building an index in the background may take slightly longer, and will still cause additional load on the system, but the database should otherwise remain available. create_index("username", background=True) As mentioned earlier in this section, MongoDB btree indexes can be used to enforce a uniqueness constraint on a particular property.

Location-based Apps with MongoDB: GeoSpatial Indexing | 33 It should be noted that at present, MongoDB’s geospatial indexing support is limited purely to point-based querying. The supplied operators can only be used for finding individual points—not routes or sub-shapes. MongoDB provides the $near and $within operators which constitute the primary means for performing geospatial queries in the system. Using $near, you can efficiently sort documents in a collection by their proximity to a given point.